Pedersen et al 2014a - Revision history

Scipediacontent at 15:16, 21 January 2021

2021-01-21T15:16:55Z

Scipediacontent: Scipediacontent moved page Draft Content 772455669 to Pedersen et al 2014a

2020-10-14T13:22:25Z

Scipediacontent moved page Draft Content 772455669 to Pedersen et al 2014a

Scipediacontent: Created page with " == Abstract == The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-54420-0_31 A large up-to-date compendium of integrated genomic data is..."

2020-10-14T13:22:23Z

Created page with " == Abstract == The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-54420-0_31 A large up-to-date compendium of integrated genomic data is..."

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== Abstract ==

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-54420-0_31 A large up-to-date compendium of integrated genomic data is often required for biological data analysis. The compendium can be tens of terabytes in size, and must often be frequently updated with new experimental or meta-data. Manual compendium update is cumbersome, requires a lot of unnecessary computation, and it may result in errors or inconsistencies in the compendium. We propose a transparent file based approach for adding incremental update ca-pabilities to unmodified genomics data analysis tools and pipeline workflow managers. This approach is implemented in the GeStore system. We evaluate GeStore using a real world genomics compendium. Our results show that it is easy to add incremental updates to genomics data processing pipelines, and that incremental updates can reduce the computation time such that it becomes prac-tical to maintain large-scale up-to-date genomics compendia on small clusters.

Document type: Part of book or chapter of book

== Full document ==
<pdf>Media:Draft_Content_772455669-beopen768-5850-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://hdl.handle.net/10037/6902 http://hdl.handle.net/10037/6902]

* [http://hdl.handle.net/10037/7563 http://hdl.handle.net/10037/7563]

* [https://hdl.handle.net/10037/6902 https://hdl.handle.net/10037/6902]

* [https://hdl.handle.net/10037/7563 https://hdl.handle.net/10037/7563]

* [https://munin.uit.no/bitstream/10037/7563/1/article.pdf https://munin.uit.no/bitstream/10037/7563/1/article.pdf]

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 The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-54420-0_31 A large up-to-date compendium of integrated genomic data is often required for biological data analysis. The compendium can be tens of terabytes in size, and must often be frequently updated with new experimental or meta-data. Manual compendium update is cumbersome, requires a lot of unnecessary computation, and it may result in errors or inconsistencies in the compendium. We propose a transparent file based approach for adding incremental update ca-pabilities to unmodified genomics data analysis tools and pipeline workflow managers. This approach is implemented in the GeStore system. We evaluate GeStore using a real world genomics compendium. Our results show that it is easy to add incremental updates to genomics data processing pipelines, and that incremental updates can reduce the computation time such that it becomes prac-tical to maintain large-scale up-to-date genomics compendia on small clusters.
@@ Line 13: / Line 8: @@
 The different versions of the original document can be found in:
 * [https://hdl.handle.net/10037/6902 https://hdl.handle.net/10037/6902]
@@ Line 23: / Line 14: @@
 * [https://munin.uit.no/bitstream/10037/7563/1/article.pdf https://munin.uit.no/bitstream/10037/7563/1/article.pdf]

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